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Soccer Analytics With Machine Learning: Learning Predictive Modeling Techniques With Sports Data - Couverture souple
Synopsis
Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game—soccer—to illuminate key concepts in predictive modeling and data science. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, you'll develop a solid foundation in machine learning through engaging examples that bridge academic principles with practical applications.
Written by experts in both machine learning and sports analytics, this practical Python-focused guide introduces fundamental data science techniques using real soccer data. Ideal for students, analysts, and soccer fans alike, it offers instructions on models and techniques such as logistic regression, random forests, deep learning, simulations, and feature engineering. But instead of memorizing algorithms, you'll learn by building predictive models to analyze match outcomes, test betting strategies, run simulated game scenarios, and more.
- Understand machine learning concepts by working with real sports data
- Develop, refine, and evaluate machine learning models, using Python for data analysis
- Carry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insights
- Apply the skills you learn to predictive modeling scenarios in other industries
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Haipeng Gao is a data science and machine learning expert with extensive industry experience building and optimizing large-scale machine learning systems at leading technology companies, including LinkedIn, TikTok, and PayPal. He holds a PhD in Statistics and Operations Research from the University of North Carolina at Chapel Hill, has taught statistics and probability at UNC Chapel Hill and San Jose State University, and holds multiple AI/ML patents granted by the U.S. Patent and Trademark Office.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data (Paperback or Softback)
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O'Reilly Media 7/21/2026, 2026
ISBN 10 : 1098181115
ISBN 13 : 9781098181116
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Soccer Analytics with Machine Learning
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Soccer Analytics with Machine Learning
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Paperback. Etat : New. Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game-soccer-to illuminate key concepts in predictive modeling and data science. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, you'll develop a solid foundation in machine learning through engaging examples that bridge academic principles with practical applications.Written by experts in both machine learning and sports analytics, this practical Python-focused guide introduces fundamental data science techniques using real soccer data. Ideal for students, analysts, and soccer fans alike, it offers instructions on models and techniques such as logistic regression, random forests, deep learning, simulations, and feature engineering. But instead of memorizing algorithms, you'll learn by building predictive models to analyze match outcomes, test betting strategies, run simulated game scenarios, and more.Understand machine learning concepts by working with real sports dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply the skills you learn to predictive modeling scenarios in other industries. N° de réf. du vendeur LU-9781098181116
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Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data
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Soccer Analytics with Machine Learning (Paperback)
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ISBN 10 : 1098181115
ISBN 13 : 9781098181116
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Paperback. Etat : new. Paperback. Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game-soccer-to illuminate key concepts in predictive modeling and data science. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, you'll develop a solid foundation in machine learning through engaging examples that bridge academic principles with practical applications.Written by experts in both machine learning and sports analytics, this practical Python-focused guide introduces fundamental data science techniques using real soccer data. Ideal for students, analysts, and soccer fans alike, it offers instructions on models and techniques such as logistic regression, random forests, deep learning, simulations, and feature engineering. But instead of memorizing algorithms, you'll learn by building predictive models to analyze match outcomes, test betting strategies, run simulated game scenarios, and more.Understand machine learning concepts by working with real sports dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply the skills you learn to predictive modeling scenarios in other industries Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game-soccer-to illuminate key concepts in predictive modeling and data science. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781098181116
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Soccer Analytics with Machine Learning
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Soccer Analytics with Machine Learning (eng)
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Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data
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Soccer Analytics with Machine Learning
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Paperback. Etat : New. Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game-soccer-to illuminate key concepts in predictive modeling and data science. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, you'll develop a solid foundation in machine learning through engaging examples that bridge academic principles with practical applications.Written by experts in both machine learning and sports analytics, this practical Python-focused guide introduces fundamental data science techniques using real soccer data. Ideal for students, analysts, and soccer fans alike, it offers instructions on models and techniques such as logistic regression, random forests, deep learning, simulations, and feature engineering. But instead of memorizing algorithms, you'll learn by building predictive models to analyze match outcomes, test betting strategies, run simulated game scenarios, and more.Understand machine learning concepts by working with real sports dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply the skills you learn to predictive modeling scenarios in other industries. N° de réf. du vendeur LU-9781098181116
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Soccer Analytics with Machine Learning
Edité par
O'Reilly Media, 2026
ISBN 10 : 1098181115
ISBN 13 : 9781098181116
Neuf
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